Module 10 Practice Questions

Front

What is a null hypothesis (Ho)?

Back

The null hypothesis (Ho) is a statement that there is no effect or no difference, and it serves as the default or starting assumption in hypothesis testing.

Front

What is an alternative hypothesis (Ha)?

Back

The alternative hypothesis (Ha) is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.

Front

What does a p-value represent in hypothesis testing?

Back

A p-value represents the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Front

What does it mean if the p-value is small (typically < 0.05)?

Back

A small p-value indicates strong evidence against the null hypothesis, leading to its rejection in favor of the alternative hypothesis.

Front

What is the significance level (alpha) in hypothesis testing?

Back

The significance level (alpha) is the threshold for determining whether to reject the null hypothesis, commonly set at 0.05.

Front

What is a Type I error?

Back

A Type I error occurs when the null hypothesis is incorrectly rejected when it is actually true.

Front

What is a Type II error?

Back

A Type II error occurs when the null hypothesis is not rejected when it is actually false.

Front

What is the purpose of hypothesis testing?

Back

The purpose of hypothesis testing is to make inferences about population parameters based on sample data.

Front

What is the difference between one-tailed and two-tailed tests?

Back

A one-tailed test assesses the direction of an effect (greater than or less than), while a two-tailed test assesses whether there is any difference (not equal to).

Front

How do you interpret a p-value of 0.22 in the context of hypothesis testing?

Back

A p-value of 0.22 suggests that there is not enough evidence to reject the null hypothesis, indicating that the observed data is consistent with the null hypothesis.